Prevention of preterm birth: Proactive and reactive clinical practice-are we on the right track?

Variation in Preterm Birth Rates Across Prenatal Care Sites in New York

OBJECTIVE

To investigate variation in preterm birth rates by the site at which prenatal care was received.

DESIGN

Cross-sectional cohort study.

SETTING

New York State.

PARTICIPANTS

Claims and encounter data on singleton live births that were covered by New York Medicaid (N = 154,377).

METHODS

We analyzed data from New York Medicaid and the American Community Survey. We established sites of prenatal care using geocoded billing addresses for prenatal visits. We calculated descriptive statistics and conducted logistic regression analyses to determine variation in crude and risk-adjusted preterm birth rates by prenatal care site.

RESULTS

The crude preterm birth rates averaged 7.8% (range = 2.0%-18.7%) by prenatal care site. The adjusted preterm birth rate was 8.0% (range = 2.8%-18.5%) by prenatal care site. Risk-adjusted preterm birth site-level rates at the 90th percentile were 2.7 times higher than those in the 10th percentile. The variation in risk-adjusted preterm birth site-level rates was not fully explained by birth volume, rural site location, or racial and ethnic composition of the patients who received prenatal care at the site.

CONCLUSION

Wide variation in risk-adjusted preterm birth rates across prenatal care sites exists, and factors beyond known individual demographics and medical factors contribute to the variation. Further research is warranted to identify why receiving care at some prenatal sites is associated with higher risk of preterm birth than receiving care at others.

Identification of biochemical biomarkers associated with premature cervical shortening in high-risk, asymptomatic pregnant women: a retrospective data analysis

Reliably predicting spontaneous preterm birth remains challenging, therefore it persists as a major contributor to perinatal morbidity and mortality. The use of biomarkers to predict premature cervical shortening, a recognised risk factor for spontaneous preterm birth, is yet to be fully explored in current literature. This study evaluates seven cervicovaginal biochemical biomarkers as possible predictors of premature cervical shortening. Asymptomatic, high-risk women (n = 131) presenting to a specialised preterm birth prevention clinic were analysed through a retrospective data analysis. Cervicovaginal biochemical biomarker concentrations were obtained, and the shortest cervical length measurement, up to 28 weeks' gestation, was recorded. Associations between biomarker concentration and cervical length were then analysed. Of the seven biochemical biomarkers, Interleukin-1 Receptor Antagonist and Extracellular Matrix Protein-1 had statistically significant relationships with cervical shortening below 25 mm. Further investigation is required to validate these findings and any downstream clinical utility, with intentions to improve perinatal outcomes.IMPACT STATEMENTWhat is already known on this subject? Preterm birth is a major cause of perinatal morbidity and mortality. A woman's risk of delivering preterm is currently stratified using historical risk factors, mid-gestation cervical length, and biochemical biomarkers such as foetal fibronectin.What do the results of this study add? In a cohort of high-risk, asymptomatic pregnant women, two cervicovaginal biochemical biomarkers, Interleukin-1 Receptor Antagonist and Extracellular Matrix Protein-1, displayed associations with premature cervical shortening.What are the implications of these findings for clinical practice and/or further research? Further investigation into the possible clinical utility of these biochemical biomarkers is warranted, with a view to improving preterm birth prediction and antenatal resource utilisation, thereby reducing the burden of preterm birth and its sequelae in a cost-effective manner.

Inflammatory Molecules Responsible for Length Shortening and Preterm Birth

It is estimated that inflammation at the placental-maternal interface is directly responsible for or contributes to the development of 50% of all premature deliveries. Chorioamnionitis, also known as the premature rupture of the amniotic membrane in the mother, is the root cause of persistent inflammation that preterm newborns experience. Beyond contributing to the onset of early labor, inflammation is a critical element in advancing several conditions in neonates, including necrotizing enterocolitis, retinopathy of prematurity, bronchopulmonary dysplasia, intraventricular hemorrhage, retinopathy of prematurity and periventricular leukomalacia. Notably, the immune systems of preterm infants are not fully developed; immune defense mechanisms and immunosuppression (tolerance) have a delicate balance that is easily upset in this patient category. As a result, premature infants are exposed to different antigens from elements such as hospital-specific microbes, artificial devices, medications, food antigens and hypoxia/hyperoxia. This has detrimental implications for preterm deliveries of less than 28 weeks because they have not yet evolved the mechanisms to tolerate maternal and self-antigens.

Contribution of labor related gene subtype classification on heterogeneity of polycystic ovary syndrome

OBJECTIVE

As one of the most common endocrine disorders in women of reproductive age, polycystic ovary syndrome (PCOS) is highly heterogeneous with varied clinical features and diverse gestational complications among individuals. The patients with PCOS have 2-fold higher risk of preterm labor which is associated with substantial infant morbidity and mortality and great socioeconomic cost. The study was designated to identify molecular subtypes and the related hub genes to facilitate the susceptibility assessment of preterm labor in women with PCOS.

METHODS

Four mRNA datasets (GSE84958, GSE5090, GSE43264 and GSE98421) were obtained from Gene Expression Omnibus database. Twenty-eight candidate genes related to preterm labor or labor were yielded from the researches and our unpublished data. Then, we utilized unsupervised clustering to identify molecular subtypes in PCOS based on the expression of above candidate genes. Key modules were generated with weighted gene co-expression network analysis R package, and their hub genes were generated with CytoHubba. The probable biological function and mechanism were explored through Gene Ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis. In addition, STRING and Cytoscape software were used to identify the protein-protein interaction (PPI) network, and the molecular complex detection (MCODE) was used to identify the hub genes. Then the overlapping hub genes were predicted.

RESULTS

Two molecular subtypes were found in women with PCOS based on the expression similarity of preterm labor or labor-related genes, in which two modules were highlighted. The key modules and PPI network have five overlapping five hub genes, two of which, GTF2F2 and MYO6 gene, were further confirmed by the comparison between clustering subgroups according to the expression of hub genes.

CONCLUSIONS

Distinct PCOS molecular subtypes were identified with preterm labor or labor-related genes, which might uncover the potential mechanism underlying heterogeneity of clinical pregnancy complications in women with PCOS.

Optimal annual body mass index change for preventing spontaneous preterm birth in a subsequent pregnancy

Preterm birth (PTB) is a leading cause of neonatal morbidity and mortality. Although PTB is known to recur, interpregnancy preventive strategies for PTB have not been established to date. Annual BMI change can serve as a specific target value for preventing obstetric complications during interpregnancy care/counseling. This value can also account for age-related weight gain (0.2 kg/m²/year). In a multicenter retrospective study, we investigated the optimal annual BMI change for preventing PTB recurrence using the data of individuals who had two singleton births from 2009 to 2019. The association between annual BMI change and spontaneous PTB (sPTB) was analyzed by separating cases of medically indicated PTB (mPTB) from those of sPTB. Previous history of sPTB was strongly associated with sPTB in the subsequent pregnancy (adjusted odds ratio [aOR], 12.7; 95% confidence interval [CI], 6.5-24.8). Increase in annual BMI was negatively associated with sPTB (aOR, 0.6; 95% CI 0.5-0.9). The sPTB recurrence rate was significantly lower in patients with an annual BMI change of ≥ 0.25 kg/m²/year than in those with an annual BMI change of < 0.25 kg/m²/year (7.7% vs. 35.0%, p = 0.011). Our findings suggest that age-related annual BMI gain between pregnancies may help prevent sPTB recurrence.

Identifying the Early Signs of Preterm Birth from U.S. Birth Records Using Machine Learning Techniques

Preterm birth (PTB) is the leading cause of infant mortality in the U.S. and globally. The goal of this study is to increase understanding of PTB risk factors that are present early in pregnancy by leveraging statistical and machine learning (ML) techniques on big data. The 2016 U.S. birth records were obtained and combined with two other area-level datasets, the Area Health Resources File and the County Health Ranking. Then, we applied logistic regression with elastic net regularization, random forest, and gradient boosting machines to study a cohort of 3.6 million singleton deliveries to identify generalizable PTB risk factors. The response variable is preterm birth, which includes spontaneous and indicated PTB, and we performed a binary classification. Our results show that the most important predictors of preterm birth are gestational and chronic hypertension, interval since last live birth, and history of a previous preterm birth, which explains 10.92, 5.98, and 5.63% of the predictive power, respectively. Parents' education is one of the influential variables in predicting PTB, explaining 7.89% of the predictive power. The relative importance of race declines when parents are more educated or have received adequate prenatal care. The gradient boosting machines outperformed with an AUC of 0.75 (sensitivity: 0.64, specificity: 0.73) for the validation dataset. In this study, we compare our results with seminal and most related studies to demonstrate the superiority of our results. The application of ML techniques improved the performance measures in the prediction of preterm birth. The results emphasize the importance of socioeconomic factors such as parental education as one of the most important indicators of preterm birth. More research is needed on these mechanisms through which socioeconomic factors affect biological responses.

Inflammation and Preterm Birth: A Systematic Review

Inflammatory mechanisms have a critical role in parturition, which results from a gathering of different stimuli that collectively initiate labour. In fact, a sophisticated interaction occurs between contractile and immuno-inflammatory pathways, whereby proinflammatory amplification is intensified by collaborative connections between cells, ligands, and tissues. Preterm birth (PTB) is one of the major challenges of modern obstetrics and still lacks an efficient treatment. Therefore, the scientific research of modern therapies is warranted. This systematic review aims to provide an overview of recent research into inflammation and PTB. The main inclusion criterion was articles concerning birth and inflammation, and searches were performed in the electronic databases MEDLINE, Embase, Scopus, Web of Science and Cochrane Library, from 2017 to 2021. A literature search from all databases yielded 1989 results which, applying the specified eligibility criteria, resulted in the 16 articles included in this review. Delivery is the consequence of an inequity between maternal inflammation and hormonal-driven uterine quiescence. Studies show that the distinction between term and preterm labour could consist of a pre-existing disproportion of decidual inflammatory signalling, or an unusual stimulus eliciting inflammatory pathways, comparable to both. Thus, controlling inflammation could be hopeful for detaining PTB.

Are pre- and early pregnancy lifestyle factors associated with the risk of preterm birth? A secondary cohort analysis of the cluster-randomised GeliS trial

Background

Maternal lifestyle is discussed as a modifiable determinant in the prevention of preterm birth. However, previous research on associations between individual lifestyle factors and preterm birth risk is inconclusive. In this secondary analysis, we investigated the associations between several modifiable antenatal lifestyle factors and the odds of preterm birth.

Methods

This secondary cohort analysis used data from the cluster-randomised controlled “healthy living in pregnancy” (GeliS) trial. Data were collected from early pregnancy to birth with maternity records, validated questionnaires and birth protocols. Women with complete datasets for all covariates were eligible for analysis. Multivariate logistic regression models, adjusted for recognised risk factors, were fitted to determine whether dietary quality, assessed with a healthy eating index (HEI), physical activity (PA) levels and antenatal anxiety/distress influenced the odds of preterm birth. Moreover, the combined association between pre-pregnancy body mass index (BMI) and HEI on the odds of preterm birth was explored. The independent associations of individual dietary components and types of PA on prematurity were assessed by adjusted logistic regression models.

Results

Overall, 1738 women were included in the analysis. A low HEI significantly increased the odds of preterm birth (OR 1.54 (CI 1.04 – 2.30), p = 0.033), while no associations with either low PA levels or antenatal anxiety/distress were observed. BMI significantly interacted with HEI on the association with prematurity (p = 0.036). Energy % from protein and the intake of average portions of vegetables and cereals were significantly negatively associated with the odds of preterm birth. There was no significant evidence of an association between different types of PA and prematurity.

Conclusions

This cohort analysis revealed that low dietary quality in early pregnancy may increase the chance of giving birth prematurely, while healthier dietary choices may help to prevent preterm birth. More research on pre- and early pregnancy modifiable lifestyle factors is warranted.

Trial registration

This trial is registered with the Clinical Trial Registry ClinicalTrials.gov (NCT01958307). Registration date 09 October 2013, retrospectively registered.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-022-04513-5.